{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dbgpt.agent.agents.planner_agent import PlannerAgent\n",
    "from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent\n",
    "from dbgpt.agent.agents.plan_group_chat import PlanChat, PlanChatManager\n",
    "\n",
    "from dbgpt.agent.agents.expand.code_assistant_agent import CodeAssistantAgent\n",
    "from dbgpt.agent.agents.expand.plugin_assistant_agent import PluginAgent\n",
    "from dbgpt.agent.agents.agents_mange import agent_mange\n",
    "\n",
    "from dbgpt.agent.agents.agent import AgentContext\n",
    "from dbgpt.agent.memory.gpts_memory import GptsMemory\n",
    "from dbgpt.core.interface.llm import ModelMetadata\n",
    "\n",
    "import asyncio\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dbgpt.model import OpenAILLMClient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "is_executing": true
   },
   "outputs": [],
   "source": [
    "# Set your api key and api base url\n",
    "# os.environ[\"OPENAI_API_KEY\"] = \"Your API\"\n",
    "# os.environ[\"OPENAI_API_BASE\"] = \"https://api.openai.com/v1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mUser\u001B[0m (to plan_manager)-[]:\n",
      "\n",
      "\"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001B[33mplan_manager\u001B[0m (to Planner)-[]:\n",
      "\n",
      "\"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: [{\n",
      "    \"serial_number\": \"1\",\n",
      "    \"agent\": \"CodeEngineer\",\n",
      "    \"content\": \"Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\",\n",
      "    \"rely\": \"\"\n",
      "},\n",
      "{\n",
      "    \"serial_number\": \"2\",\n",
      "    \"agent\": \"CodeEngineer\",\n",
      "    \"content\": \"Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\",\n",
      "    \"rely\": \"1\"\n",
      "}]\n",
      "\u001B[33mPlanner\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"[{\\n    \\\"serial_number\\\": \\\"1\\\",\\n    \\\"agent\\\": \\\"CodeEngineer\\\",\\n    \\\"content\\\": \\\"Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\\\",\\n    \\\"rely\\\": \\\"\\\"\\n},\\n{\\n    \\\"serial_number\\\": \\\"2\\\",\\n    \\\"agent\\\": \\\"CodeEngineer\\\",\\n    \\\"content\\\": \\\"Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\\\",\\n    \\\"rely\\\": \\\"1\\\"\\n}]\"\n",
      "\u001B[32m>>>>>>>>Planner Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>Planner Action report: \n",
      "execution succeeded,\n",
      "1,Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\n",
      "2,Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GroupChat is underpopulated with 1 agents. It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False.Or, use direct communication instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mplan_manager\u001B[0m (to CodeEngineer)-[]:\n",
      "\n",
      "\"Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: ```python\n",
      "# filename: github_issues.py\n",
      "import requests\n",
      "from datetime import datetime, timedelta\n",
      "\n",
      "# Function to get issues created in the past three days from a GitHub repository\n",
      "def get_recent_issues(owner, repo):\n",
      "    # Calculate the date for three days ago\n",
      "    three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "    # Format the date in ISO 8601 format\n",
      "    since = three_days_ago.isoformat()\n",
      "\n",
      "    # GitHub API URL for issues of the given repository\n",
      "    issues_url = f\"https://api.github.com/repos/{owner}/{repo}/issues\"\n",
      "    \n",
      "    # Parameters to get issues created in the past three days\n",
      "    params = {\n",
      "        'since': since,\n",
      "        'state': 'all',  # Get both open and closed issues\n",
      "    }\n",
      "    \n",
      "    # Send a request to the GitHub API\n",
      "    response = requests.get(issues_url, params=params)\n",
      "    # Raise an exception if the request was unsuccessful\n",
      "    response.raise_for_status()\n",
      "    \n",
      "    # Parse the JSON response\n",
      "    issues = response.json()\n",
      "    \n",
      "    # Extract and print the creation date and status of each issue\n",
      "    for issue in issues:\n",
      "        created_at = issue['created_at']\n",
      "        state = issue['state']\n",
      "        print(f\"Issue created at: {created_at}, Status: {state}\")\n",
      "\n",
      "# Replace 'owner' and 'repo' with the actual owner and repository name\n",
      "get_recent_issues('eosphoros-ai', 'DB-GPT')\n",
      "```\n",
      "\n",
      "When you run this script, it will print out the creation date and status of issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. Make sure to have internet access while running the script as it needs to make requests to the GitHub API.\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001B[0m\n",
      "\u001B[33mCodeEngineer\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"```python\\n# filename: github_issues.py\\nimport requests\\nfrom datetime import datetime, timedelta\\n\\n# Function to get issues created in the past three days from a GitHub repository\\ndef get_recent_issues(owner, repo):\\n    # Calculate the date for three days ago\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\n    # Format the date in ISO 8601 format\\n    since = three_days_ago.isoformat()\\n\\n    # GitHub API URL for issues of the given repository\\n    issues_url = f\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\"\\n    \\n    # Parameters to get issues created in the past three days\\n    params = {\\n        'since': since,\\n        'state': 'all',  # Get both open and closed issues\\n    }\\n    \\n    # Send a request to the GitHub API\\n    response = requests.get(issues_url, params=params)\\n    # Raise an exception if the request was unsuccessful\\n    response.raise_for_status()\\n    \\n    # Parse the JSON response\\n    issues = response.json()\\n    \\n    # Extract and print the creation date and status of each issue\\n    for issue in issues:\\n        created_at = issue['created_at']\\n        state = issue['state']\\n        print(f\\\"Issue created at: {created_at}, Status: {state}\\\")\\n\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\n```\\n\\nWhen you run this script, it will print out the creation date and status of issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. Make sure to have internet access while running the script as it needs to make requests to the GitHub API.\"\n",
      "\u001B[32m>>>>>>>>CodeEngineer Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>CodeEngineer Action report: \n",
      "execution failed,\n",
      "exitcode: 1 (execution failed)\n",
      " \n",
      "Traceback (most recent call last):\n",
      "  File \"github_issues.py\", line 2, in <module>\n",
      "    import requests\n",
      "ModuleNotFoundError: No module named 'requests'\n",
      "\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GroupChat is underpopulated with 1 agents. It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False.Or, use direct communication instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mplan_manager\u001B[0m (to CodeEngineer)-[]:\n",
      "\n",
      "\"exitcode: 1 (execution failed)\\n \\nTraceback (most recent call last):\\n  File \\\"github_issues.py\\\", line 2, in <module>\\n    import requests\\nModuleNotFoundError: No module named 'requests'\\n\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: It appears that the `requests` module is not installed on your system. You can install it using `pip`, the Python package manager. Here's the command to install the `requests` module:\n",
      "\n",
      "```sh\n",
      "pip install requests\n",
      "```\n",
      "\n",
      "After installing the `requests` module, you can try running the script again. Here is the complete script including the installation of the `requests` module:\n",
      "\n",
      "```python\n",
      "# filename: github_issues.py\n",
      "import requests\n",
      "from datetime import datetime, timedelta\n",
      "\n",
      "# Function to get issues created in the past three days from a GitHub repository\n",
      "def get_recent_issues(owner, repo):\n",
      "    # Calculate the date for three days ago\n",
      "    three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "    # Format the date in ISO 8601 format\n",
      "    since = three_days_ago.isoformat()\n",
      "\n",
      "    # GitHub API URL for issues of the given repository\n",
      "    issues_url = f\"https://api.github.com/repos/{owner}/{repo}/issues\"\n",
      "    \n",
      "    # Parameters to get issues created in the past three days\n",
      "    params = {\n",
      "        'since': since,\n",
      "        'state': 'all',  # Get both open and closed issues\n",
      "    }\n",
      "    \n",
      "    # Send a request to the GitHub API\n",
      "    response = requests.get(issues_url, params=params)\n",
      "    # Raise an exception if the request was unsuccessful\n",
      "    response.raise_for_status()\n",
      "    \n",
      "    # Parse the JSON response\n",
      "    issues = response.json()\n",
      "    \n",
      "    # Extract and print the creation date and status of each issue\n",
      "    for issue in issues:\n",
      "        created_at = issue['created_at']\n",
      "        state = issue['state']\n",
      "        print(f\"Issue created at: {created_at}, Status: {state}\")\n",
      "\n",
      "# Replace 'owner' and 'repo' with the actual owner and repository name\n",
      "get_recent_issues('eosphoros-ai', 'DB-GPT')\n",
      "```\n",
      "\n",
      "Please run the above Python script after you have installed the `requests` module.\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001B[0m\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 1 (inferred language is python)...\u001B[0m\n",
      "un_stream ai response: False\n",
      "\u001B[33mCodeEngineer\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"It appears that the `requests` module is not installed on your system. You can install it using `pip`, the Python package manager. Here's the command to install the `requests` module:\\n\\n```sh\\npip install requests\\n```\\n\\nAfter installing the `requests` module, you can try running the script again. Here is the complete script including the installation of the `requests` module:\\n\\n```python\\n# filename: github_issues.py\\nimport requests\\nfrom datetime import datetime, timedelta\\n\\n# Function to get issues created in the past three days from a GitHub repository\\ndef get_recent_issues(owner, repo):\\n    # Calculate the date for three days ago\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\n    # Format the date in ISO 8601 format\\n    since = three_days_ago.isoformat()\\n\\n    # GitHub API URL for issues of the given repository\\n    issues_url = f\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\"\\n    \\n    # Parameters to get issues created in the past three days\\n    params = {\\n        'since': since,\\n        'state': 'all',  # Get both open and closed issues\\n    }\\n    \\n    # Send a request to the GitHub API\\n    response = requests.get(issues_url, params=params)\\n    # Raise an exception if the request was unsuccessful\\n    response.raise_for_status()\\n    \\n    # Parse the JSON response\\n    issues = response.json()\\n    \\n    # Extract and print the creation date and status of each issue\\n    for issue in issues:\\n        created_at = issue['created_at']\\n        state = issue['state']\\n        print(f\\\"Issue created at: {created_at}, Status: {state}\\\")\\n\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\n```\\n\\nPlease run the above Python script after you have installed the `requests` module.\"\n",
      "\u001B[32m>>>>>>>>CodeEngineer Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>CodeEngineer Action report: \n",
      "execution succeeded,\n",
      "\n",
      "Collecting requests\n",
      "  Obtaining dependency information for requests from https://files.pythonhosted.org/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl.metadata\n",
      "  Downloading requests-2.31.0-py3-none-any.whl.metadata (4.6 kB)\n",
      "Collecting charset-normalizer<4,>=2 (from requests)\n",
      "  Obtaining dependency information for charset-normalizer<4,>=2 from https://files.pythonhosted.org/packages/45/59/3d27019d3b447a88fe7e7d004a1e04be220227760264cc41b405e863891b/charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl.metadata\n",
      "  Downloading charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl.metadata (33 kB)\n",
      "Collecting idna<4,>=2.5 (from requests)\n",
      "  Obtaining dependency information for idna<4,>=2.5 from https://files.pythonhosted.org/packages/c2/e7/a82b05cf63a603df6e68d59ae6a68bf5064484a0718ea5033660af4b54a9/idna-3.6-py3-none-any.whl.metadata\n",
      "  Downloading idna-3.6-py3-none-any.whl.metadata (9.9 kB)\n",
      "Collecting urllib3<3,>=1.21.1 (from requests)\n",
      "  Obtaining dependency information for urllib3<3,>=1.21.1 from https://files.pythonhosted.org/packages/96/94/c31f58c7a7f470d5665935262ebd7455c7e4c7782eb525658d3dbf4b9403/urllib3-2.1.0-py3-none-any.whl.metadata\n",
      "  Downloading urllib3-2.1.0-py3-none-any.whl.metadata (6.4 kB)\n",
      "Collecting certifi>=2017.4.17 (from requests)\n",
      "  Obtaining dependency information for certifi>=2017.4.17 from https://files.pythonhosted.org/packages/64/62/428ef076be88fa93716b576e4a01f919d25968913e817077a386fcbe4f42/certifi-2023.11.17-py3-none-any.whl.metadata\n",
      "  Downloading certifi-2023.11.17-py3-none-any.whl.metadata (2.2 kB)\n",
      "Downloading requests-2.31.0-py3-none-any.whl (62 kB)\n",
      "   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.6/62.6 kB 1.9 MB/s eta 0:00:00\n",
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      "Downloading idna-3.6-py3-none-any.whl (61 kB)\n",
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      "Downloading urllib3-2.1.0-py3-none-any.whl (104 kB)\n",
      "   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 104.6/104.6 kB 4.9 MB/s eta 0:00:00\n",
      "Installing collected packages: urllib3, idna, charset-normalizer, certifi, requests\n",
      "Successfully installed certifi-2023.11.17 charset-normalizer-3.3.2 idna-3.6 requests-2.31.0 urllib3-2.1.0\n",
      "WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\n",
      "\n",
      "[notice] A new release of pip is available: 23.2.1 -> 23.3.2\n",
      "[notice] To update, run: pip install --upgrade pip\n",
      "\n",
      "/workspace/github_issues.py:8: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\n",
      "  three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "Issue created at: 2023-12-27T03:20:12Z, Status: open\n",
      "Issue created at: 2023-12-26T16:13:42Z, Status: open\n",
      "Issue created at: 2023-12-26T10:23:43Z, Status: open\n",
      "Issue created at: 2023-12-26T07:25:37Z, Status: closed\n",
      "Issue created at: 2023-12-26T05:01:26Z, Status: closed\n",
      "Issue created at: 2023-12-26T03:54:15Z, Status: open\n",
      "Issue created at: 2023-12-26T02:19:48Z, Status: open\n",
      "Issue created at: 2023-12-25T12:26:40Z, Status: open\n",
      "Issue created at: 2023-12-25T12:00:52Z, Status: open\n",
      "Issue created at: 2023-12-25T08:36:56Z, Status: open\n",
      "Issue created at: 2023-12-25T08:35:48Z, Status: open\n",
      "Issue created at: 2023-12-25T08:34:13Z, Status: closed\n",
      "Issue created at: 2023-12-25T06:33:37Z, Status: closed\n",
      "Issue created at: 2023-12-23T11:47:40Z, Status: closed\n",
      "Issue created at: 2023-12-23T03:01:23Z, Status: open\n",
      "Issue created at: 2023-12-19T06:38:57Z, Status: open\n",
      "Issue created at: 2023-12-11T08:34:08Z, Status: open\n",
      "Issue created at: 2023-11-26T03:55:22Z, Status: open\n",
      "Issue created at: 2023-11-25T12:38:23Z, Status: open\n",
      "Issue created at: 2023-11-25T02:25:13Z, Status: open\n",
      "Issue created at: 2023-11-25T02:09:58Z, Status: open\n",
      "Issue created at: 2023-11-24T08:48:24Z, Status: open\n",
      "Issue created at: 2023-11-24T06:03:56Z, Status: open\n",
      "Issue created at: 2023-11-23T16:25:33Z, Status: open\n",
      "Issue created at: 2023-11-23T08:54:36Z, Status: open\n",
      "Issue created at: 2023-11-23T08:26:27Z, Status: open\n",
      "Issue created at: 2023-11-22T06:42:34Z, Status: open\n",
      "Issue created at: 2023-10-26T01:45:37Z, Status: open\n",
      "Issue created at: 2023-08-30T06:02:32Z, Status: closed\n",
      "Issue created at: 2023-06-18T01:11:22Z, Status: open\n",
      "\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GroupChat is underpopulated with 1 agents. It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False.Or, use direct communication instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mplan_manager\u001B[0m (to CodeEngineer)-[]:\n",
      "\n",
      "\"The execution result of the code you wrote is judged as not answering the task question. Please re-understand and complete the task.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: I apologize for the inconvenience. Let me provide you with a Python script that includes a check to ensure the `requests` module is installed. If it's not installed, the script will attempt to install it using `pip`. Please run the following Python script:\n",
      "\n",
      "```python\n",
      "# filename: github_issues.py\n",
      "import subprocess\n",
      "import pkg_resources\n",
      "from datetime import datetime, timedelta\n",
      "\n",
      "# Ensure the 'requests' package is installed\n",
      "required_packages = {'requests'}\n",
      "installed_packages = {pkg.key for pkg in pkg_resources.working_set}\n",
      "missing_packages = required_packages - installed_packages\n",
      "\n",
      "if missing_packages:\n",
      "    subprocess.check_call(['pip', 'install', *missing_packages])\n",
      "\n",
      "import requests\n",
      "\n",
      "# Function to get issues created in the past three days from a GitHub repository\n",
      "def get_recent_issues(owner, repo):\n",
      "    # Calculate the date for three days ago\n",
      "    three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "    # Format the date in ISO 8601 format\n",
      "    since = three_days_ago.isoformat()\n",
      "\n",
      "    # GitHub API URL for issues of the given repository\n",
      "    issues_url = f\"https://api.github.com/repos/{owner}/{repo}/issues\"\n",
      "    \n",
      "    # Parameters to get issues created in the past three days\n",
      "    params = {\n",
      "        'since': since,\n",
      "        'state': 'all',  # Get both open and closed issues\n",
      "    }\n",
      "    \n",
      "    # Send a request to the GitHub API\n",
      "    response = requests.get(issues_url, params=params)\n",
      "    # Raise an exception if the request was unsuccessful\n",
      "    response.raise_for_status()\n",
      "    \n",
      "    # Parse the JSON response\n",
      "    issues = response.json()\n",
      "    \n",
      "    # Extract and print the creation date and status of each issue\n",
      "    for issue in issues:\n",
      "        created_at = issue['created_at']\n",
      "        state = issue['state']\n",
      "        print(f\"Issue created at: {created_at}, Status: {state}\")\n",
      "\n",
      "# Replace 'owner' and 'repo' with the actual owner and repository name\n",
      "get_recent_issues('eosphoros-ai', 'DB-GPT')\n",
      "```\n",
      "\n",
      "When you run this script, it will check for the `requests` module and install it if necessary. Then it will retrieve the issues from the 'eosphoros-ai/DB-GPT' repository created in the past three days and print their creation date and status.\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001B[0m\n",
      "un_stream ai response: False\n",
      "\u001B[33mCodeEngineer\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"I apologize for the inconvenience. Let me provide you with a Python script that includes a check to ensure the `requests` module is installed. If it's not installed, the script will attempt to install it using `pip`. Please run the following Python script:\\n\\n```python\\n# filename: github_issues.py\\nimport subprocess\\nimport pkg_resources\\nfrom datetime import datetime, timedelta\\n\\n# Ensure the 'requests' package is installed\\nrequired_packages = {'requests'}\\ninstalled_packages = {pkg.key for pkg in pkg_resources.working_set}\\nmissing_packages = required_packages - installed_packages\\n\\nif missing_packages:\\n    subprocess.check_call(['pip', 'install', *missing_packages])\\n\\nimport requests\\n\\n# Function to get issues created in the past three days from a GitHub repository\\ndef get_recent_issues(owner, repo):\\n    # Calculate the date for three days ago\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\n    # Format the date in ISO 8601 format\\n    since = three_days_ago.isoformat()\\n\\n    # GitHub API URL for issues of the given repository\\n    issues_url = f\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\"\\n    \\n    # Parameters to get issues created in the past three days\\n    params = {\\n        'since': since,\\n        'state': 'all',  # Get both open and closed issues\\n    }\\n    \\n    # Send a request to the GitHub API\\n    response = requests.get(issues_url, params=params)\\n    # Raise an exception if the request was unsuccessful\\n    response.raise_for_status()\\n    \\n    # Parse the JSON response\\n    issues = response.json()\\n    \\n    # Extract and print the creation date and status of each issue\\n    for issue in issues:\\n        created_at = issue['created_at']\\n        state = issue['state']\\n        print(f\\\"Issue created at: {created_at}, Status: {state}\\\")\\n\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\n```\\n\\nWhen you run this script, it will check for the `requests` module and install it if necessary. Then it will retrieve the issues from the 'eosphoros-ai/DB-GPT' repository created in the past three days and print their creation date and status.\"\n",
      "\u001B[32m>>>>>>>>CodeEngineer Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>CodeEngineer Action report: \n",
      "execution succeeded,\n",
      "\n",
      "/workspace/github_issues.py:3: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n",
      "  import pkg_resources\n",
      "/workspace/github_issues.py:19: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\n",
      "  three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "Issue created at: 2023-12-27T03:20:12Z, Status: open\n",
      "Issue created at: 2023-12-26T16:13:42Z, Status: open\n",
      "Issue created at: 2023-12-26T10:23:43Z, Status: open\n",
      "Issue created at: 2023-12-26T07:25:37Z, Status: closed\n",
      "Issue created at: 2023-12-26T05:01:26Z, Status: closed\n",
      "Issue created at: 2023-12-26T03:54:15Z, Status: open\n",
      "Issue created at: 2023-12-26T02:19:48Z, Status: open\n",
      "Issue created at: 2023-12-25T12:26:40Z, Status: open\n",
      "Issue created at: 2023-12-25T12:00:52Z, Status: open\n",
      "Issue created at: 2023-12-25T08:36:56Z, Status: open\n",
      "Issue created at: 2023-12-25T08:35:48Z, Status: open\n",
      "Issue created at: 2023-12-25T08:34:13Z, Status: closed\n",
      "Issue created at: 2023-12-25T06:33:37Z, Status: closed\n",
      "Issue created at: 2023-12-23T11:47:40Z, Status: closed\n",
      "Issue created at: 2023-12-23T03:01:23Z, Status: open\n",
      "Issue created at: 2023-12-19T06:38:57Z, Status: open\n",
      "Issue created at: 2023-12-11T08:34:08Z, Status: open\n",
      "Issue created at: 2023-11-26T03:55:22Z, Status: open\n",
      "Issue created at: 2023-11-25T12:38:23Z, Status: open\n",
      "Issue created at: 2023-11-25T02:25:13Z, Status: open\n",
      "Issue created at: 2023-11-25T02:09:58Z, Status: open\n",
      "Issue created at: 2023-11-24T08:48:24Z, Status: open\n",
      "Issue created at: 2023-11-24T06:03:56Z, Status: open\n",
      "Issue created at: 2023-11-23T16:25:33Z, Status: open\n",
      "Issue created at: 2023-11-23T08:54:36Z, Status: open\n",
      "Issue created at: 2023-11-23T08:26:27Z, Status: open\n",
      "Issue created at: 2023-11-22T06:42:34Z, Status: open\n",
      "Issue created at: 2023-10-26T01:45:37Z, Status: open\n",
      "Issue created at: 2023-08-30T06:02:32Z, Status: closed\n",
      "Issue created at: 2023-06-18T01:11:22Z, Status: open\n",
      "\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GroupChat is underpopulated with 1 agents. It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False.Or, use direct communication instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mplan_manager\u001B[0m (to CodeEngineer)-[]:\n",
      "\n",
      "\"The execution result of the code you wrote is judged as not answering the task question. Please re-understand and complete the task.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: I apologize for the oversight. Let's try a different approach to ensure we get the issues created in the past three days from the 'eosphoros-ai/DB-GPT' repository. I will provide you with an updated Python script that correctly retrieves and filters the issues based on their creation date.\n",
      "\n",
      "```python\n",
      "# filename: github_issues.py\n",
      "import requests\n",
      "from datetime import datetime, timedelta\n",
      "\n",
      "# Function to get issues created in the past three days from a GitHub repository\n",
      "def get_recent_issues(owner, repo):\n",
      "    # Calculate the date for three days ago\n",
      "    three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "    # Format the date in ISO 8601 format\n",
      "    since = three_days_ago.isoformat()\n",
      "\n",
      "    # GitHub API URL for issues of the given repository\n",
      "    issues_url = f\"https://api.github.com/repos/{owner}/{repo}/issues\"\n",
      "\n",
      "    # Parameters to get all issues, GitHub API does not allow filtering by creation date directly\n",
      "    params = {\n",
      "        'state': 'all',  # Get both open and closed issues\n",
      "    }\n",
      "\n",
      "    # Send a request to the GitHub API\n",
      "    response = requests.get(issues_url, params=params)\n",
      "    # Raise an exception if the request was unsuccessful\n",
      "    response.raise_for_status()\n",
      "\n",
      "    # Parse the JSON response\n",
      "    issues = response.json()\n",
      "\n",
      "    # Filter and print the creation date and status of each issue created in the past three days\n",
      "    for issue in issues:\n",
      "        created_at = datetime.strptime(issue['created_at'], \"%Y-%m-%dT%H:%M:%SZ\")\n",
      "        if created_at > three_days_ago:\n",
      "            state = issue['state']\n",
      "            print(f\"Issue created at: {created_at}, Status: {state}\")\n",
      "\n",
      "# Replace 'owner' and 'repo' with the actual owner and repository name\n",
      "get_recent_issues('eosphoros-ai', 'DB-GPT')\n",
      "```\n",
      "\n",
      "This script retrieves all issues from the specified repository and then filters them based on the creation date to find the ones that were created in the past three days. It then prints the creation date and status of each issue that meets the criteria. Please execute this updated script.\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001B[0m\n",
      "un_stream ai response: True\n",
      "\u001B[33mCodeEngineer\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"I apologize for the oversight. Let's try a different approach to ensure we get the issues created in the past three days from the 'eosphoros-ai/DB-GPT' repository. I will provide you with an updated Python script that correctly retrieves and filters the issues based on their creation date.\\n\\n```python\\n# filename: github_issues.py\\nimport requests\\nfrom datetime import datetime, timedelta\\n\\n# Function to get issues created in the past three days from a GitHub repository\\ndef get_recent_issues(owner, repo):\\n    # Calculate the date for three days ago\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\n    # Format the date in ISO 8601 format\\n    since = three_days_ago.isoformat()\\n\\n    # GitHub API URL for issues of the given repository\\n    issues_url = f\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\"\\n\\n    # Parameters to get all issues, GitHub API does not allow filtering by creation date directly\\n    params = {\\n        'state': 'all',  # Get both open and closed issues\\n    }\\n\\n    # Send a request to the GitHub API\\n    response = requests.get(issues_url, params=params)\\n    # Raise an exception if the request was unsuccessful\\n    response.raise_for_status()\\n\\n    # Parse the JSON response\\n    issues = response.json()\\n\\n    # Filter and print the creation date and status of each issue created in the past three days\\n    for issue in issues:\\n        created_at = datetime.strptime(issue['created_at'], \\\"%Y-%m-%dT%H:%M:%SZ\\\")\\n        if created_at > three_days_ago:\\n            state = issue['state']\\n            print(f\\\"Issue created at: {created_at}, Status: {state}\\\")\\n\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\n```\\n\\nThis script retrieves all issues from the specified repository and then filters them based on the creation date to find the ones that were created in the past three days. It then prints the creation date and status of each issue that meets the criteria. Please execute this updated script.\"\n",
      "\u001B[32m>>>>>>>>CodeEngineer Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>CodeEngineer Action report: \n",
      "execution succeeded,\n",
      "\n",
      "/workspace/github_issues.py:8: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\n",
      "  three_days_ago = datetime.utcnow() - timedelta(days=3)\n",
      "Issue created at: 2023-12-27 03:20:12, Status: open\n",
      "Issue created at: 2023-12-26 16:13:42, Status: open\n",
      "Issue created at: 2023-12-26 10:23:43, Status: open\n",
      "Issue created at: 2023-12-26 07:25:37, Status: closed\n",
      "Issue created at: 2023-12-26 05:01:26, Status: closed\n",
      "Issue created at: 2023-12-26 03:54:15, Status: open\n",
      "Issue created at: 2023-12-26 02:19:48, Status: open\n",
      "Issue created at: 2023-12-25 12:26:40, Status: open\n",
      "Issue created at: 2023-12-25 12:00:52, Status: open\n",
      "Issue created at: 2023-12-25 08:36:56, Status: open\n",
      "Issue created at: 2023-12-25 08:35:48, Status: open\n",
      "Issue created at: 2023-12-25 08:34:13, Status: closed\n",
      "Issue created at: 2023-12-25 06:33:37, Status: closed\n",
      "\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GroupChat is underpopulated with 1 agents. It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False.Or, use direct communication instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001B[33mplan_manager\u001B[0m (to CodeEngineer)-[]:\n",
      "\n",
      "\"Read the result data of the dependent steps in the above historical message to complete the current goal:Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\"\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "un_stream ai response: ```python\n",
      "# Let's process the retrieved issues data to group them by creation date and status.\n",
      "# Then, we will format the grouped data into a Markdown table.\n",
      "\n",
      "# The data from the previous step\n",
      "issues_data = [\n",
      "    {\"created_at\": \"2023-12-27 03:20:12\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-26 16:13:42\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-26 10:23:43\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-26 07:25:37\", \"status\": \"closed\"},\n",
      "    {\"created_at\": \"2023-12-26 05:01:26\", \"status\": \"closed\"},\n",
      "    {\"created_at\": \"2023-12-26 03:54:15\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-26 02:19:48\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-25 12:26:40\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-25 12:00:52\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-25 08:36:56\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-25 08:35:48\", \"status\": \"open\"},\n",
      "    {\"created_at\": \"2023-12-25 08:34:13\", \"status\": \"closed\"},\n",
      "    {\"created_at\": \"2023-12-25 06:33:37\", \"status\": \"closed\"},\n",
      "]\n",
      "\n",
      "# Grouping the issues by creation date and status\n",
      "from collections import defaultdict\n",
      "grouped_issues = defaultdict(lambda: defaultdict(list))\n",
      "\n",
      "for issue in issues_data:\n",
      "    date = issue[\"created_at\"].split(' ')[0]  # Extract just the date part\n",
      "    grouped_issues[date][issue[\"status\"]].append(issue)\n",
      "\n",
      "# Format the grouped data into a Markdown table\n",
      "markdown_table = \"Date | Open Issues | Closed Issues\\n\"\n",
      "markdown_table += \"--- | --- | ---\\n\"\n",
      "\n",
      "for date, statuses in sorted(grouped_issues.items()):\n",
      "    open_issues = len(statuses[\"open\"]) if \"open\" in statuses else 0\n",
      "    closed_issues = len(statuses[\"closed\"]) if \"closed\" in statuses else 0\n",
      "    markdown_table += f\"{date} | {open_issues} | {closed_issues}\\n\"\n",
      "\n",
      "print(markdown_table)\n",
      "```\n",
      "\n",
      "When you run this script, it will print out a Markdown table with the number of open and closed issues grouped by their creation dates.\n",
      "\u001B[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001B[0m\n",
      "un_stream ai response: True\n",
      "\u001B[33mCodeEngineer\u001B[0m (to plan_manager)-[gpt-4-vision-preview]:\n",
      "\n",
      "\"```python\\n# Let's process the retrieved issues data to group them by creation date and status.\\n# Then, we will format the grouped data into a Markdown table.\\n\\n# The data from the previous step\\nissues_data = [\\n    {\\\"created_at\\\": \\\"2023-12-27 03:20:12\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 16:13:42\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 10:23:43\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 07:25:37\\\", \\\"status\\\": \\\"closed\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 05:01:26\\\", \\\"status\\\": \\\"closed\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 03:54:15\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-26 02:19:48\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 12:26:40\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 12:00:52\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 08:36:56\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 08:35:48\\\", \\\"status\\\": \\\"open\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 08:34:13\\\", \\\"status\\\": \\\"closed\\\"},\\n    {\\\"created_at\\\": \\\"2023-12-25 06:33:37\\\", \\\"status\\\": \\\"closed\\\"},\\n]\\n\\n# Grouping the issues by creation date and status\\nfrom collections import defaultdict\\ngrouped_issues = defaultdict(lambda: defaultdict(list))\\n\\nfor issue in issues_data:\\n    date = issue[\\\"created_at\\\"].split(' ')[0]  # Extract just the date part\\n    grouped_issues[date][issue[\\\"status\\\"]].append(issue)\\n\\n# Format the grouped data into a Markdown table\\nmarkdown_table = \\\"Date | Open Issues | Closed Issues\\\\n\\\"\\nmarkdown_table += \\\"--- | --- | ---\\\\n\\\"\\n\\nfor date, statuses in sorted(grouped_issues.items()):\\n    open_issues = len(statuses[\\\"open\\\"]) if \\\"open\\\" in statuses else 0\\n    closed_issues = len(statuses[\\\"closed\\\"]) if \\\"closed\\\" in statuses else 0\\n    markdown_table += f\\\"{date} | {open_issues} | {closed_issues}\\\\n\\\"\\n\\nprint(markdown_table)\\n```\\n\\nWhen you run this script, it will print out a Markdown table with the number of open and closed issues grouped by their creation dates.\"\n",
      "\u001B[32m>>>>>>>>CodeEngineer Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>CodeEngineer Action report: \n",
      "execution succeeded,\n",
      "\n",
      "Date | Open Issues | Closed Issues\n",
      "--- | --- | ---\n",
      "2023-12-25 | 4 | 2\n",
      "2023-12-26 | 4 | 2\n",
      "2023-12-27 | 1 | 0\n",
      "\n",
      "\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001B[33mplan_manager\u001B[0m (to User)-[None]:\n",
      "\n",
      "\"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\"\n",
      "\u001B[32m>>>>>>>>plan_manager Review info: \n",
      " Pass.None\u001B[0m\n",
      "\u001B[34m>>>>>>>>plan_manager Action report: \n",
      "execution succeeded,\n",
      "TERMINATE\u001B[0m\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "```agent-messages\n",
      "[{\"sender\": \"User\", \"receiver\": \"plan_manager\", \"model\": null, \"markdown\": \"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\"}, {\"sender\": \"plan_manager\", \"receiver\": \"Planner\", \"model\": null, \"markdown\": \"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\"}, {\"sender\": \"Planner\", \"receiver\": \"plan_manager\", \"model\": \"gpt-4-vision-preview\", \"markdown\": \"1,Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\\n2,Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\"}, {\"sender\": \"plan_manager\", \"receiver\": \"User\", \"model\": null, \"markdown\": \"TERMINATE\"}]\n",
      "```\n",
      "```agent-plans\n",
      "[{\"name\": \"Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\", \"num\": \"1\", \"status\": \"complete\", \"agent\": \"CodeEngineer\", \"markdown\": \"```agent-messages\\n[{\\\"sender\\\": \\\"plan_manager\\\", \\\"receiver\\\": \\\"CodeEngineer\\\", \\\"model\\\": null, \\\"markdown\\\": \\\"Write a Python script to use the GitHub API to retrieve issues from the 'eosphoros-ai/DB-GPT' repository that were created in the past three days. The script should extract the issue's creation date and status.\\\"}, {\\\"sender\\\": \\\"CodeEngineer\\\", \\\"receiver\\\": \\\"plan_manager\\\", \\\"model\\\": \\\"gpt-4-vision-preview\\\", \\\"markdown\\\": \\\"```vis-code\\\\n{\\\\\\\"exit_success\\\\\\\": false, \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\", \\\\\\\"code\\\\\\\": [[\\\\\\\"python\\\\\\\", \\\\\\\"# filename: github_issues.py\\\\\\\\nimport requests\\\\\\\\nfrom datetime import datetime, timedelta\\\\\\\\n\\\\\\\\n# Function to get issues created in the past three days from a GitHub repository\\\\\\\\ndef get_recent_issues(owner, repo):\\\\\\\\n    # Calculate the date for three days ago\\\\\\\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\n    # Format the date in ISO 8601 format\\\\\\\\n    since = three_days_ago.isoformat()\\\\\\\\n\\\\\\\\n    # GitHub API URL for issues of the given repository\\\\\\\\n    issues_url = f\\\\\\\\\\\\\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\\\\\\\\\\\\\"\\\\\\\\n    \\\\\\\\n    # Parameters to get issues created in the past three days\\\\\\\\n    params = {\\\\\\\\n        'since': since,\\\\\\\\n        'state': 'all',  # Get both open and closed issues\\\\\\\\n    }\\\\\\\\n    \\\\\\\\n    # Send a request to the GitHub API\\\\\\\\n    response = requests.get(issues_url, params=params)\\\\\\\\n    # Raise an exception if the request was unsuccessful\\\\\\\\n    response.raise_for_status()\\\\\\\\n    \\\\\\\\n    # Parse the JSON response\\\\\\\\n    issues = response.json()\\\\\\\\n    \\\\\\\\n    # Extract and print the creation date and status of each issue\\\\\\\\n    for issue in issues:\\\\\\\\n        created_at = issue['created_at']\\\\\\\\n        state = issue['state']\\\\\\\\n        print(f\\\\\\\\\\\\\\\"Issue created at: {created_at}, Status: {state}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\\\\\\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\\\\\\"]], \\\\\\\"log\\\\\\\": \\\\\\\"\\\\\\\\nTraceback (most recent call last):\\\\\\\\n  File \\\\\\\\\\\\\\\"github_issues.py\\\\\\\\\\\\\\\", line 2, in <module>\\\\\\\\n    import requests\\\\\\\\nModuleNotFoundError: No module named 'requests'\\\\\\\\n\\\\\\\"}\\\\n```\\\"}, {\\\"sender\\\": \\\"plan_manager\\\", \\\"receiver\\\": \\\"CodeEngineer\\\", \\\"model\\\": null, \\\"markdown\\\": \\\"exitcode: 1 (execution failed)\\\\n \\\\nTraceback (most recent call last):\\\\n  File \\\\\\\"github_issues.py\\\\\\\", line 2, in <module>\\\\n    import requests\\\\nModuleNotFoundError: No module named 'requests'\\\\n\\\"}, {\\\"sender\\\": \\\"CodeEngineer\\\", \\\"receiver\\\": \\\"plan_manager\\\", \\\"model\\\": \\\"gpt-4-vision-preview\\\", \\\"markdown\\\": \\\"```vis-code\\\\n{\\\\\\\"exit_success\\\\\\\": true, \\\\\\\"language\\\\\\\": \\\\\\\"sh\\\\\\\", \\\\\\\"code\\\\\\\": [[\\\\\\\"sh\\\\\\\", \\\\\\\"pip install requests\\\\\\\"], [\\\\\\\"python\\\\\\\", \\\\\\\"# filename: github_issues.py\\\\\\\\nimport requests\\\\\\\\nfrom datetime import datetime, timedelta\\\\\\\\n\\\\\\\\n# Function to get issues created in the past three days from a GitHub repository\\\\\\\\ndef get_recent_issues(owner, repo):\\\\\\\\n    # Calculate the date for three days ago\\\\\\\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\n    # Format the date in ISO 8601 format\\\\\\\\n    since = three_days_ago.isoformat()\\\\\\\\n\\\\\\\\n    # GitHub API URL for issues of the given repository\\\\\\\\n    issues_url = f\\\\\\\\\\\\\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\\\\\\\\\\\\\"\\\\\\\\n    \\\\\\\\n    # Parameters to get issues created in the past three days\\\\\\\\n    params = {\\\\\\\\n        'since': since,\\\\\\\\n        'state': 'all',  # Get both open and closed issues\\\\\\\\n    }\\\\\\\\n    \\\\\\\\n    # Send a request to the GitHub API\\\\\\\\n    response = requests.get(issues_url, params=params)\\\\\\\\n    # Raise an exception if the request was unsuccessful\\\\\\\\n    response.raise_for_status()\\\\\\\\n    \\\\\\\\n    # Parse the JSON response\\\\\\\\n    issues = response.json()\\\\\\\\n    \\\\\\\\n    # Extract and print the creation date and status of each issue\\\\\\\\n    for issue in issues:\\\\\\\\n        created_at = issue['created_at']\\\\\\\\n        state = issue['state']\\\\\\\\n        print(f\\\\\\\\\\\\\\\"Issue created at: {created_at}, Status: {state}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\\\\\\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\\\\\\"]], \\\\\\\"log\\\\\\\": \\\\\\\"\\\\\\\\nCollecting requests\\\\\\\\n  Obtaining dependency information for requests from https://files.pythonhosted.org/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl.metadata\\\\\\\\n  Downloading requests-2.31.0-py3-none-any.whl.metadata (4.6 kB)\\\\\\\\nCollecting charset-normalizer<4,>=2 (from requests)\\\\\\\\n  Obtaining dependency information for charset-normalizer<4,>=2 from https://files.pythonhosted.org/packages/45/59/3d27019d3b447a88fe7e7d004a1e04be220227760264cc41b405e863891b/charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl.metadata\\\\\\\\n  Downloading charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl.metadata (33 kB)\\\\\\\\nCollecting idna<4,>=2.5 (from requests)\\\\\\\\n  Obtaining dependency information for idna<4,>=2.5 from https://files.pythonhosted.org/packages/c2/e7/a82b05cf63a603df6e68d59ae6a68bf5064484a0718ea5033660af4b54a9/idna-3.6-py3-none-any.whl.metadata\\\\\\\\n  Downloading idna-3.6-py3-none-any.whl.metadata (9.9 kB)\\\\\\\\nCollecting urllib3<3,>=1.21.1 (from requests)\\\\\\\\n  Obtaining dependency information for urllib3<3,>=1.21.1 from https://files.pythonhosted.org/packages/96/94/c31f58c7a7f470d5665935262ebd7455c7e4c7782eb525658d3dbf4b9403/urllib3-2.1.0-py3-none-any.whl.metadata\\\\\\\\n  Downloading urllib3-2.1.0-py3-none-any.whl.metadata (6.4 kB)\\\\\\\\nCollecting certifi>=2017.4.17 (from requests)\\\\\\\\n  Obtaining dependency information for certifi>=2017.4.17 from https://files.pythonhosted.org/packages/64/62/428ef076be88fa93716b576e4a01f919d25968913e817077a386fcbe4f42/certifi-2023.11.17-py3-none-any.whl.metadata\\\\\\\\n  Downloading certifi-2023.11.17-py3-none-any.whl.metadata (2.2 kB)\\\\\\\\nDownloading requests-2.31.0-py3-none-any.whl (62 kB)\\\\\\\\n   \\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501 62.6/62.6 kB 1.9 MB/s eta 0:00:00\\\\\\\\nDownloading certifi-2023.11.17-py3-none-any.whl (162 kB)\\\\\\\\n   \\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501 162.5/162.5 kB 1.9 MB/s eta 0:00:00\\\\\\\\nDownloading charset_normalizer-3.3.2-cp312-cp312-musllinux_1_1_aarch64.whl (138 kB)\\\\\\\\n   \\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501 138.3/138.3 kB 4.6 MB/s eta 0:00:00\\\\\\\\nDownloading idna-3.6-py3-none-any.whl (61 kB)\\\\\\\\n   \\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501 61.6/61.6 kB 3.2 MB/s eta 0:00:00\\\\\\\\nDownloading urllib3-2.1.0-py3-none-any.whl (104 kB)\\\\\\\\n   \\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501\\\\\\\\u2501 104.6/104.6 kB 4.9 MB/s eta 0:00:00\\\\\\\\nInstalling collected packages: urllib3, idna, charset-normalizer, certifi, requests\\\\\\\\nSuccessfully installed certifi-2023.11.17 charset-normalizer-3.3.2 idna-3.6 requests-2.31.0 urllib3-2.1.0\\\\\\\\nWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\\\\\\\\n\\\\\\\\n[notice] A new release of pip is available: 23.2.1 -> 23.3.2\\\\\\\\n[notice] To update, run: pip install --upgrade pip\\\\\\\\n\\\\\\\\n/workspace/github_issues.py:8: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\\\\\\\\n  three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\nIssue created at: 2023-12-27T03:20:12Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T16:13:42Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T10:23:43Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T07:25:37Z, Status: closed\\\\\\\\nIssue created at: 2023-12-26T05:01:26Z, Status: closed\\\\\\\\nIssue created at: 2023-12-26T03:54:15Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T02:19:48Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T12:26:40Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T12:00:52Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:36:56Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:35:48Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:34:13Z, Status: closed\\\\\\\\nIssue created at: 2023-12-25T06:33:37Z, Status: closed\\\\\\\\nIssue created at: 2023-12-23T11:47:40Z, Status: closed\\\\\\\\nIssue created at: 2023-12-23T03:01:23Z, Status: open\\\\\\\\nIssue created at: 2023-12-19T06:38:57Z, Status: open\\\\\\\\nIssue created at: 2023-12-11T08:34:08Z, Status: open\\\\\\\\nIssue created at: 2023-11-26T03:55:22Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T12:38:23Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T02:25:13Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T02:09:58Z, Status: open\\\\\\\\nIssue created at: 2023-11-24T08:48:24Z, Status: open\\\\\\\\nIssue created at: 2023-11-24T06:03:56Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T16:25:33Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T08:54:36Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T08:26:27Z, Status: open\\\\\\\\nIssue created at: 2023-11-22T06:42:34Z, Status: open\\\\\\\\nIssue created at: 2023-10-26T01:45:37Z, Status: open\\\\\\\\nIssue created at: 2023-08-30T06:02:32Z, Status: closed\\\\\\\\nIssue created at: 2023-06-18T01:11:22Z, Status: open\\\\\\\\n\\\\\\\"}\\\\n```\\\"}, {\\\"sender\\\": \\\"plan_manager\\\", \\\"receiver\\\": \\\"CodeEngineer\\\", \\\"model\\\": null, \\\"markdown\\\": \\\"The execution result of the code you wrote is judged as not answering the task question. Please re-understand and complete the task.\\\"}, {\\\"sender\\\": \\\"CodeEngineer\\\", \\\"receiver\\\": \\\"plan_manager\\\", \\\"model\\\": \\\"gpt-4-vision-preview\\\", \\\"markdown\\\": \\\"```vis-code\\\\n{\\\\\\\"exit_success\\\\\\\": true, \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\", \\\\\\\"code\\\\\\\": [[\\\\\\\"python\\\\\\\", \\\\\\\"# filename: github_issues.py\\\\\\\\nimport subprocess\\\\\\\\nimport pkg_resources\\\\\\\\nfrom datetime import datetime, timedelta\\\\\\\\n\\\\\\\\n# Ensure the 'requests' package is installed\\\\\\\\nrequired_packages = {'requests'}\\\\\\\\ninstalled_packages = {pkg.key for pkg in pkg_resources.working_set}\\\\\\\\nmissing_packages = required_packages - installed_packages\\\\\\\\n\\\\\\\\nif missing_packages:\\\\\\\\n    subprocess.check_call(['pip', 'install', *missing_packages])\\\\\\\\n\\\\\\\\nimport requests\\\\\\\\n\\\\\\\\n# Function to get issues created in the past three days from a GitHub repository\\\\\\\\ndef get_recent_issues(owner, repo):\\\\\\\\n    # Calculate the date for three days ago\\\\\\\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\n    # Format the date in ISO 8601 format\\\\\\\\n    since = three_days_ago.isoformat()\\\\\\\\n\\\\\\\\n    # GitHub API URL for issues of the given repository\\\\\\\\n    issues_url = f\\\\\\\\\\\\\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\\\\\\\\\\\\\"\\\\\\\\n    \\\\\\\\n    # Parameters to get issues created in the past three days\\\\\\\\n    params = {\\\\\\\\n        'since': since,\\\\\\\\n        'state': 'all',  # Get both open and closed issues\\\\\\\\n    }\\\\\\\\n    \\\\\\\\n    # Send a request to the GitHub API\\\\\\\\n    response = requests.get(issues_url, params=params)\\\\\\\\n    # Raise an exception if the request was unsuccessful\\\\\\\\n    response.raise_for_status()\\\\\\\\n    \\\\\\\\n    # Parse the JSON response\\\\\\\\n    issues = response.json()\\\\\\\\n    \\\\\\\\n    # Extract and print the creation date and status of each issue\\\\\\\\n    for issue in issues:\\\\\\\\n        created_at = issue['created_at']\\\\\\\\n        state = issue['state']\\\\\\\\n        print(f\\\\\\\\\\\\\\\"Issue created at: {created_at}, Status: {state}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\\\\\\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\\\\\\"]], \\\\\\\"log\\\\\\\": \\\\\\\"\\\\\\\\n/workspace/github_issues.py:3: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\\\\\\\\n  import pkg_resources\\\\\\\\n/workspace/github_issues.py:19: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\\\\\\\\n  three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\nIssue created at: 2023-12-27T03:20:12Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T16:13:42Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T10:23:43Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T07:25:37Z, Status: closed\\\\\\\\nIssue created at: 2023-12-26T05:01:26Z, Status: closed\\\\\\\\nIssue created at: 2023-12-26T03:54:15Z, Status: open\\\\\\\\nIssue created at: 2023-12-26T02:19:48Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T12:26:40Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T12:00:52Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:36:56Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:35:48Z, Status: open\\\\\\\\nIssue created at: 2023-12-25T08:34:13Z, Status: closed\\\\\\\\nIssue created at: 2023-12-25T06:33:37Z, Status: closed\\\\\\\\nIssue created at: 2023-12-23T11:47:40Z, Status: closed\\\\\\\\nIssue created at: 2023-12-23T03:01:23Z, Status: open\\\\\\\\nIssue created at: 2023-12-19T06:38:57Z, Status: open\\\\\\\\nIssue created at: 2023-12-11T08:34:08Z, Status: open\\\\\\\\nIssue created at: 2023-11-26T03:55:22Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T12:38:23Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T02:25:13Z, Status: open\\\\\\\\nIssue created at: 2023-11-25T02:09:58Z, Status: open\\\\\\\\nIssue created at: 2023-11-24T08:48:24Z, Status: open\\\\\\\\nIssue created at: 2023-11-24T06:03:56Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T16:25:33Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T08:54:36Z, Status: open\\\\\\\\nIssue created at: 2023-11-23T08:26:27Z, Status: open\\\\\\\\nIssue created at: 2023-11-22T06:42:34Z, Status: open\\\\\\\\nIssue created at: 2023-10-26T01:45:37Z, Status: open\\\\\\\\nIssue created at: 2023-08-30T06:02:32Z, Status: closed\\\\\\\\nIssue created at: 2023-06-18T01:11:22Z, Status: open\\\\\\\\n\\\\\\\"}\\\\n```\\\"}, {\\\"sender\\\": \\\"plan_manager\\\", \\\"receiver\\\": \\\"CodeEngineer\\\", \\\"model\\\": null, \\\"markdown\\\": \\\"The execution result of the code you wrote is judged as not answering the task question. Please re-understand and complete the task.\\\"}, {\\\"sender\\\": \\\"CodeEngineer\\\", \\\"receiver\\\": \\\"plan_manager\\\", \\\"model\\\": \\\"gpt-4-vision-preview\\\", \\\"markdown\\\": \\\"```vis-code\\\\n{\\\\\\\"exit_success\\\\\\\": true, \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\", \\\\\\\"code\\\\\\\": [[\\\\\\\"python\\\\\\\", \\\\\\\"# filename: github_issues.py\\\\\\\\nimport requests\\\\\\\\nfrom datetime import datetime, timedelta\\\\\\\\n\\\\\\\\n# Function to get issues created in the past three days from a GitHub repository\\\\\\\\ndef get_recent_issues(owner, repo):\\\\\\\\n    # Calculate the date for three days ago\\\\\\\\n    three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\n    # Format the date in ISO 8601 format\\\\\\\\n    since = three_days_ago.isoformat()\\\\\\\\n\\\\\\\\n    # GitHub API URL for issues of the given repository\\\\\\\\n    issues_url = f\\\\\\\\\\\\\\\"https://api.github.com/repos/{owner}/{repo}/issues\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\\n    # Parameters to get all issues, GitHub API does not allow filtering by creation date directly\\\\\\\\n    params = {\\\\\\\\n        'state': 'all',  # Get both open and closed issues\\\\\\\\n    }\\\\\\\\n\\\\\\\\n    # Send a request to the GitHub API\\\\\\\\n    response = requests.get(issues_url, params=params)\\\\\\\\n    # Raise an exception if the request was unsuccessful\\\\\\\\n    response.raise_for_status()\\\\\\\\n\\\\\\\\n    # Parse the JSON response\\\\\\\\n    issues = response.json()\\\\\\\\n\\\\\\\\n    # Filter and print the creation date and status of each issue created in the past three days\\\\\\\\n    for issue in issues:\\\\\\\\n        created_at = datetime.strptime(issue['created_at'], \\\\\\\\\\\\\\\"%Y-%m-%dT%H:%M:%SZ\\\\\\\\\\\\\\\")\\\\\\\\n        if created_at > three_days_ago:\\\\\\\\n            state = issue['state']\\\\\\\\n            print(f\\\\\\\\\\\\\\\"Issue created at: {created_at}, Status: {state}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\n# Replace 'owner' and 'repo' with the actual owner and repository name\\\\\\\\nget_recent_issues('eosphoros-ai', 'DB-GPT')\\\\\\\"]], \\\\\\\"log\\\\\\\": \\\\\\\"\\\\\\\\n/workspace/github_issues.py:8: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).\\\\\\\\n  three_days_ago = datetime.utcnow() - timedelta(days=3)\\\\\\\\nIssue created at: 2023-12-27 03:20:12, Status: open\\\\\\\\nIssue created at: 2023-12-26 16:13:42, Status: open\\\\\\\\nIssue created at: 2023-12-26 10:23:43, Status: open\\\\\\\\nIssue created at: 2023-12-26 07:25:37, Status: closed\\\\\\\\nIssue created at: 2023-12-26 05:01:26, Status: closed\\\\\\\\nIssue created at: 2023-12-26 03:54:15, Status: open\\\\\\\\nIssue created at: 2023-12-26 02:19:48, Status: open\\\\\\\\nIssue created at: 2023-12-25 12:26:40, Status: open\\\\\\\\nIssue created at: 2023-12-25 12:00:52, Status: open\\\\\\\\nIssue created at: 2023-12-25 08:36:56, Status: open\\\\\\\\nIssue created at: 2023-12-25 08:35:48, Status: open\\\\\\\\nIssue created at: 2023-12-25 08:34:13, Status: closed\\\\\\\\nIssue created at: 2023-12-25 06:33:37, Status: closed\\\\\\\\n\\\\\\\"}\\\\n```\\\"}]\\n```\"}, {\"name\": \"Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\", \"num\": \"2\", \"status\": \"complete\", \"agent\": \"CodeEngineer\", \"markdown\": \"```agent-messages\\n[{\\\"sender\\\": \\\"plan_manager\\\", \\\"receiver\\\": \\\"CodeEngineer\\\", \\\"model\\\": null, \\\"markdown\\\": \\\"Read the result data of the dependent steps in the above historical message to complete the current goal:Write a Python script to process the retrieved issues data to group them by creation date and status. Then, format the grouped data into a Markdown table.\\\"}, {\\\"sender\\\": \\\"CodeEngineer\\\", \\\"receiver\\\": \\\"plan_manager\\\", \\\"model\\\": \\\"gpt-4-vision-preview\\\", \\\"markdown\\\": \\\"```vis-code\\\\n{\\\\\\\"exit_success\\\\\\\": true, \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\", \\\\\\\"code\\\\\\\": [[\\\\\\\"python\\\\\\\", \\\\\\\"# Let's process the retrieved issues data to group them by creation date and status.\\\\\\\\n# Then, we will format the grouped data into a Markdown table.\\\\\\\\n\\\\\\\\n# The data from the previous step\\\\\\\\nissues_data = [\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-27 03:20:12\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 16:13:42\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 10:23:43\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 07:25:37\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 05:01:26\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 03:54:15\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-26 02:19:48\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 12:26:40\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 12:00:52\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 08:36:56\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 08:35:48\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 08:34:13\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\"},\\\\\\\\n    {\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"2023-12-25 06:33:37\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\"},\\\\\\\\n]\\\\\\\\n\\\\\\\\n# Grouping the issues by creation date and status\\\\\\\\nfrom collections import defaultdict\\\\\\\\ngrouped_issues = defaultdict(lambda: defaultdict(list))\\\\\\\\n\\\\\\\\nfor issue in issues_data:\\\\\\\\n    date = issue[\\\\\\\\\\\\\\\"created_at\\\\\\\\\\\\\\\"].split(' ')[0]  # Extract just the date part\\\\\\\\n    grouped_issues[date][issue[\\\\\\\\\\\\\\\"status\\\\\\\\\\\\\\\"]].append(issue)\\\\\\\\n\\\\\\\\n# Format the grouped data into a Markdown table\\\\\\\\nmarkdown_table = \\\\\\\\\\\\\\\"Date | Open Issues | Closed Issues\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\"\\\\\\\\nmarkdown_table += \\\\\\\\\\\\\\\"--- | --- | ---\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\\nfor date, statuses in sorted(grouped_issues.items()):\\\\\\\\n    open_issues = len(statuses[\\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\"]) if \\\\\\\\\\\\\\\"open\\\\\\\\\\\\\\\" in statuses else 0\\\\\\\\n    closed_issues = len(statuses[\\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\"]) if \\\\\\\\\\\\\\\"closed\\\\\\\\\\\\\\\" in statuses else 0\\\\\\\\n    markdown_table += f\\\\\\\\\\\\\\\"{date} | {open_issues} | {closed_issues}\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\\nprint(markdown_table)\\\\\\\"]], \\\\\\\"log\\\\\\\": \\\\\\\"\\\\\\\\nDate | Open Issues | Closed Issues\\\\\\\\n--- | --- | ---\\\\\\\\n2023-12-25 | 4 | 2\\\\\\\\n2023-12-26 | 4 | 2\\\\\\\\n2023-12-27 | 1 | 0\\\\\\\\n\\\\\\\\n\\\\\\\"}\\\\n```\\\"}]\\n```\"}]\n",
      "```\n"
     ]
    }
   ],
   "source": [
    "llm_client = OpenAILLMClient()\n",
    "context: AgentContext = AgentContext(conv_id=\"test\", llm_provider=llm_client)\n",
    "# context.llm_models = [ModelMetadata(model=\"gpt-3.5-turbo\")]\n",
    "context.llm_models = [ModelMetadata(model=\"gpt-4-vision-preview\")]\n",
    "context.gpts_name = \"代码分析助手\"\n",
    "\n",
    "default_memory = GptsMemory()\n",
    "coder = CodeAssistantAgent(memory=default_memory, agent_context=context)\n",
    "## TODO  add other agent\n",
    "\n",
    "groupchat = PlanChat(agents=[coder], messages=[], max_round=50)\n",
    "planner = PlannerAgent(\n",
    "    agent_context=context,\n",
    "    memory=default_memory,\n",
    "    plan_chat=groupchat,\n",
    ")\n",
    "\n",
    "manager = PlanChatManager(\n",
    "    plan_chat=groupchat,\n",
    "    planner=planner,\n",
    "    agent_context=context,\n",
    "    memory=default_memory,\n",
    ")\n",
    "\n",
    "user_proxy = UserProxyAgent(memory=default_memory, agent_context=context)\n",
    "\n",
    "\n",
    "await user_proxy.a_initiate_chat(\n",
    "        recipient=manager,\n",
    "        reviewer=user_proxy,\n",
    "        message=\"Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.\",\n",
    "        # message=\"Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table\",\n",
    "        # message=\"find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.\",\n",
    "    )\n",
    "\n"
   ]
  }
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